Senior Analytics Engineer at PandaDoc

Warsaw, Masovian Voivodeship, Poland -

Full Time

Start Date

Immediate

Expiry Date

26 Apr, 26

Salary

0.0

Posted On

26 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, dbt, Snowflake, Data Cataloging, Data Orchestration, Python, Dimensional Modeling, SaaS Metrics, GitHub, Data Quality, Data Governance, Data Documentation, Analytics Engineering, Data Transformation, Customer Journey Analysis, Revenue Analytics

Industry

Software Development

Description

Company Overview PandaDoc empowers more than 60,000 growing organizations to thrive by taking the work out of document workflow. PandaDoc provides an all-in-one document workflow automation platform that helps fast scaling teams accelerate the ability to create, manage, and sign digital documents including proposals, quotes, contracts, and more. For more information, please visit https://www.pandadoc.com. About the Role We're looking for a Senior Analytics Engineer to join our data team at PandaDoc. In this role, you'll be at the intersection of data engineering and analytics, building the foundational data models and infrastructure that power insights across the organization. You'll work closely with data analysts, business stakeholders, and engineering teams to transform raw data into trusted, accessible datasets that drive strategic decisions around customer success, revenue growth, and product development. About the PandaDoc Data Platform You'll be working with a best-in-class modern data stack that reflects industry-leading practices. Our infrastructure is built on Snowflake as our cloud data warehouse, with dbt powering our transformation layer and Select Star providing comprehensive data cataloging and discovery. We've implemented robust data governance practices including PII auditing and data quality monitoring via Monte Carlo. Our platform integrates data from across the business—including Salesforce, HubSpot, Recurly, and our product databases—creating a unified view of customer journeys, subscription metrics, and product usage. We're actively exploring cutting-edge technologies like composable CDPs, reverse ETL with Hightouch, and event analytics with PostHog. The data team has a strong partnership with business stakeholders, regularly delivering high-impact analyses that drive decisions around customer expansion, payment gateway adoption, and product strategy. You'll have the autonomy to influence our architecture decisions and help shape our evolution toward an AI-enabled, domain-oriented data organization. What You'll Do Design, build, and maintain dimensional data models in Snowflake that serve as the foundation for analytics and reporting across the company Develop and optimize dbt models to transform raw data from systems like Salesforce, HubSpot, Recurly, and other business platforms into clean, reliable datasets Create and maintain data documentation in Select Star and other catalog tools to ensure discoverability and understanding of our data assets Partner with data analysts and business teams to understand their analytical needs and translate them into scalable data solutions Implement data quality checks and monitoring to ensure accuracy and reliability of analytics datasets Optimize SQL queries and data pipelines for performance and cost efficiency Support strategic analytics initiatives including customer journey analysis, revenue analytics, and product usage metrics Contribute to data governance practices including data quality standards, PII handling, and metadata management Mentor junior team members and promote best practices in data modeling and analytics engineering What You'll Bring 5+ years of experience in analytics engineering, data engineering, or similar data-focused role Expert-level SQL skills with experience writing complex queries, CTEs, and window functions Strong experience with dbt (data build tool) for building and maintaining transformation pipelines Hands-on experience with Snowflake or other cloud data warehouses (e.g. BigQuery, Redshift) Familiarity with data cataloging tools (Select Star preferred) Knowledge of data orchestration tools (Airflow / MWAA preferred) Strong background in Python for data analysis or automation Deep understanding of dimensional modeling, data warehouse design patterns, and analytics best practices Experience working with SaaS metrics (MRR, churn, customer lifetime value, etc.) Proficiency with GitHub for version control and collaborative development Strong communication skills with ability to translate technical concepts for business stakeholders Self-directed and comfortable working in a remote environment with distributed teams Nice to Have Experience with reverse ETL tools such as Hightouch Some exposure to BI tools (Hex preferred) Understanding of data mesh or domain-oriented data architecture concepts Company Culture We're known for our work-life balance, kind co-workers, & creative virtual team-bonding events. And although our Pandas are located across the globe, we stay connected with the help of technology and ensure that everyone on our team feels, well, like a team. Pandas work best when they're happy. We retain our talent by upholding our values of integrity & transparency, and selling a product that changes the lives of our customers. Our attainment of awards such as Best Workplace, Best StartUp Employer and a Stevie Award for Best Employers demonstrate our commitment to our culture. Check out LinkedIn to learn more. Benefits Remote-first approach with the option for hybrid work from our offices in Kyiv, Warsaw, and Lisbon. We value long-term collaboration, whether through typical employment contract, employment of record or B2B arrangements. Be aware that contract type and benefits vary by location - feel free to clarify with our recruiters). Work schedule aligned with EU time zones. Honest, open culture that values constructive feedback. Professional and personal development within a collaborative, supportive team. Stable yet growing SaaS product offering an agile environment, ownership, start-up energy, and strong technical challenges.

Responsibilities

The Senior Analytics Engineer will design, build, and maintain dimensional data models in Snowflake and develop dbt models to transform raw data into reliable datasets. They will also partner with data analysts and business teams to create scalable data solutions and implement data quality checks.